Selecting analytical biomarkers for diagnostic applications: a first principles approach

Introduction: Biomarkers are objective indications of a medical state that can be measured accurately and reproducibly. Traditional biomarkers enable diagnosis of disease through detection of disease-specific molecules, disease-mediated molecular changes, or distinct physiological or anatomical signatures.

Areas covered: This work provides a framework for selecting biomarkers that are most likely to provide useful information about a patient’s disease state. Though the authors emphasize markers related to disease, this work is also applicable to biomarkers for monitoring physiological changes such as ovulation or pregnancy. Additionally, the scope was restricted to biomarkers that are amenable to analytical detection across a range of health care levels, including low resource settings. The authors describe trade-offs between biomarkers’ sensitivity/specificity for a disease-causing agent, the complexity of detection, and how this knowledge can be applied to the development of diagnostic tests. This report also details additional assessment criteria for successful tests.

Expert commentary: Biomarker selection should primarily be driven by an attempt to answer an explicit clinical question (preferably causative relationship of the biomarker to disease-state), and only then by test development expediency (ease of detection). This framework is useful for stakeholders from test developers to clinicians to identify the trade-offs for diagnostic biomarkers for any use case.